Gesture recognition using Microsoft Kinect®

Gesture recognition is essential for human — machine interaction. In this paper we propose a method to recognize human gestures using a Kinect® depth camera. The camera views the subject in the front plane and generates a depth image of the subject in the plane towards the camera. This depth image is then used for background removal, followed by generation of the depth profile of the subject. In addition to this, the difference between subsequent frames gives the motion profile of the subject and is used for recognition of gestures. These allow the efficient use of depth camera to successfully recognize multiple human gestures. The result of a case study involving 8 gestures is shown. The system was trained using a multi class Support Vector Machine.

[1]  Kikuo Fujimura,et al.  A Bayesian Framework for Human Body Pose Tracking from Depth Image Sequences , 2010, Sensors.

[2]  Yong Rui,et al.  Segmenting visual actions based on spatio-temporal motion patterns , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[3]  Stefan Müller,et al.  Hand Gesture Recognition with a Novel IR Time-of-Flight Range Camera-A Pilot Study , 2007, MIRAGE.

[4]  Jake K. Aggarwal,et al.  Using head movement to recognize activity , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[5]  Jake K. Aggarwal,et al.  Segmentation and recognition of continuous human activity , 2001, Proceedings IEEE Workshop on Detection and Recognition of Events in Video.

[6]  T. W. Ridler,et al.  Picture thresholding using an iterative selection method. , 1978 .

[7]  Tae-Seong Kim,et al.  Human Activity Recognition via 3-D joint angle features and Hidden Markov models , 2010, 2010 IEEE International Conference on Image Processing.